Distributed ARTMAP: a neural network for fast distributed supervised learning

نویسندگان

  • Gail A. Carpenter
  • Boriana L. Milenova
  • Benjamin W. Noeske
چکیده

Distributed coding at the hidden layer of a multi-layer perceptron (MLP) endows the network with memory compression and noise tolerance capabilities. However, an MLP typically requires slow off-line learning to avoid catastrophic forgetting in an open input environment. An adaptive resonance theory (ART) model is designed to guarantee stable memories even with fast on-line learning. However, ART stability typically requires winner-take-all coding, which may cause category proliferation in a noisy input environment. Distributed ARTMAP (dARTMAP) seeks to combine the computational advantages of MLP and ART systems in a real-time neural network for supervised learning. An implementation algorithm here describes one class of dARTMAP networks. This system incorporates elements of the unsupervised dART model, as well as new features, including a content-addressable memory (CAM) rule for improved contrast control at the coding field. A dARTMAP system reduces to fuzzy ARTMAP when coding is winner-take-all. Simulations show that dARTMAP retains fuzzy ARTMAP accuracy while significantly improving memory compression.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Distributed ARTMAP

Distributed coding at the hidden layer of a multi–layer perceptron (MLP) endows the network with memory compression and noise tolerance capabilities. However, an MLP typically requires slow off–line learning to avoid catastrophic forgetting in an open input environment. An adaptive resonance theory (ART) model is designed to guarantee stable memories even with fast on–line learning. However, AR...

متن کامل

Distributed ARTMAP - Neural Networks, 1999. IJCNN '99. International Joint Conference on

Distributed coding at the hidden layer of a multi-layer perceptron (&UP) endows the network with memory compression and noise tolerance capabilities. However, an MLP typically requires slow o&line learning to avoid catastrophic forgetting in an open input environment. An adaptive resonance theory (ART) model i3 designed to guarantee stable memories even with fast on-line learning. However, ART ...

متن کامل

Self-supervised ARTMAP

Computational models of learning typically train on labeled input patterns (supervised learning), unlabeled input patterns (unsupervised learning), or a combination of the two (semi-supervised learning). In each case input patterns have a fixed number of features throughout training and testing. Human and machine learning contexts present additional opportunities for expanding incomplete knowle...

متن کامل

ART Neural Networks for Medical Data Analysis and Fast Distributed Learning

ART (Adaptive Resonance Theory) neural networks for fast, stable learning and prediction have been applied in a variety of areas. Applications include airplane design and manufacturing, automatic target recognition, financial forecasting, machine tool monitoring, digital circuit design, chemical analysis, and robot vision. Supervised ART architectures, called ARTMAP systems, feature internal co...

متن کامل

Default ARTMAP 2 - Technical Report

Default ARTMAP combines winner-take-all category node activation during training, distributed activation during testing, and a set of default parameter values that define a ready-to-use, general-purpose neural network system for supervised learning and recognition. Winner-take-all ARTMAP learning is designed so that each input would make a correct prediction if re-presented immediately after it...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Neural networks : the official journal of the International Neural Network Society

دوره 11 5  شماره 

صفحات  -

تاریخ انتشار 1998